brl1906 / fmdview Goto Github PK

1. update layout to create 3 rows with 3 columns each:

• row 1 charts: volume scatter, scatter map, choropleth map
• row 2 charts: heatmap week, heatmap month, dual donut chart on work order distribution
• row 3 charts: open close line chart, multi axis subplots top is current week or month parameter dependent current status on kpi and bottom chart is yearly barchart. (make one for ontime and one for pm 2 cm.

Remove the block of commented out code in the data.py module that is at the bottom of the filter_fiscalyear function. It represents an older thought about how to implement and should be removed to reduce clutter.

1. Find the data.py module
2. Find the filter_fiscalyear function.
3. Identify the commented out code and remove it.

1. Add 2 week SMA to line chart on open & closed.
2. leave markers for SMA as traces to filter on or off for all other frequencies
3. make chart view options:

• 2weeks SMA

• daily, weekly, monthly, annually

1. test app in newvenv
2. change name of newvenv to venv-fmdview
3. update requirements.txt file

add detailed docstring, project consistent format.

rename use me to instructions and add code snippets to instructions for ease of installation

1. add map to charts.py module that maps work order request volume onto a chloropleth map to show number of work order reqeusts by city council district
2. add a year filter for all or for individual fiscal year (parameter)
3. add a view filter or option to show colorscale by volume or by pct closed on time (parameter)

1. add hyperlink for each section.

1. Rename chart function to make more clear
2. Add docstring to chart creating function

1. find open vs completed chart function in chart.py module
2. move labels horizontal below chart or to a place that doesn't overlap with chart title

Build a small data pipeline or function(s) that:

1. gets updated data
2. renders charts using the updated data

call connected Archibus sheet
open and update the sheet
push the sheet to datadotworld
call datadotworld to get data to move through the functions

1. find open_vs_completed chart generating function in charts.py
2. add functionality that determines if the frequency parameter is 'D' or daily and if so,
   change the trace hovertext so that it displays the date and number open and closed in a pretty format , for example:

• May 3, 2017

• opened: 45

• May 3, 2017

• completed: 44

In module with clean_datafame function:

1. add a get_data function that makes the call to data.world
2. in the clean_dataframe function add a logging event that follows the implementation from the twitterbot project logs.
3. log date, levelname, module, function, status

1. identify core elements in app.py
2. see manufactoring plotly dashboard model for example of how to compartmentalize

1. in chart.py module
2. find open vs completed backlog charting function
3. style hovertext using list comprehension to create bold and line break hovertext formatting

remove todo

connect the view or filter between charts 1 and 2.

Remove unwanted icons in charts.

1. make list widgets for each chart
2. update layout to include/remove charts for each layout

1. In the weekday_complete and month_complete functions in chart.py module change the formatting of the z value hovertext so that it displays 13% instead of 12.999555 , for example.
2. consider better function names for these heatmap generators displaying count and percentage of work orders completed in a given time frame (day or month)

1. move charts from app.py to charts.py
2. refactor charts
3. create well defined adn documented sections for charts and each

4. create a chart class and initialze each chart as an instance of a main chart Class.

1. refactor the heatmap weekday_complete and month_complete to include hour and week.

2. bring this together in one function using separate functions to check the value of z_value argument in the function and call that function within the larger function to handle the separate cases. (See Clean Code, Robert Martin chapter on making good functions for guidance here.)